Cleanliness evaluation in sputter targets using phase

ABSTRACT

An improved method and apparatus for non-destructive cleanliness evaluation in sputter targets using radio frequency waveform phase change and amplitude detection is disclosed. The apparatus acquires phase change and amplitude for a plurality of data points. The method disclosed for characterizing the sputter target material ( 52 ) employs the phase change and amplitude magnitude data for calculating cleanliness factors and generating pareto histograms.

CROSS-REFERENCE TO RELATED APPLICATIONS

Priority filing benefit of (1) International PCT applicationPCT/US01/14403 filed May 4, 2001, and published under PCT 21(2) in theEnglish language and (2) U.S. provisional application Serial No.60/203,568 filed May 11, 2000.

FIELD OF THE INVENTION

This invention relates to non-destructive testing methods and apparatusfor identifying types of intrinsic flaws in metallic sputter targetmaterials and, more particularly, non-destructive methods and apparatusfor identifying and counting of solid inclusions using radio frequencyecho waveform phase change detection.

BACKGROUND OF THE INVENTION

Cathodic sputtering is widely used for depositing thin layers or filmsof materials from sputter targets onto desired substrates such assemiconductor wafers. Basically, a cathode assembly including a sputtertarget is placed together with an anode in a chamber filled with aninert gas, preferably argon. The desired substrate is positioned in thechamber near the anode with a receiving surface oriented normal to apath between the cathode assembly and the anode. A high voltage electricfield is applied across the cathode assembly and the anode.

Electrons ejected from the cathode assembly ionize the inert gas. Theelectrical field then propels positively charged ions of the inert gasagainst a sputtering surface of the sputter target. Material dislodgedfrom the sputter target by the ion bombardment traverses the chamber anddeposits on the receiving surface of the substrate to form the thinlayer or film.

One factor affecting the quality of the layer or film produced by asputtering process is the “cleanliness” of the material from which thesputter target is made. The term “cleanliness” is widely used in thesemiconductor industry, among others, to characterize high purity andultra high purity materials. In common practice, “cleanliness” refers tothe degree of material internal purity. Such impurities may be present,for example, as traces of foreign elements in distributed or localizedform in the sputter target material. Cleanliness is usually measured inunits of particles per million (“ppm”) or particles per billion (“ppb”)which define a ratio between the number of contaminant atoms and thetotal number of atoms sampled.

Since the cleanliness of the material from which a sputter target ismade affects the quality of layers of films produced using that target,it is obviously desirable to use relatively clean materials infabricating sputter targets. This implies a need in the art fornon-destructive techniques for selecting sputter target blanks ofsuitable cleanliness to produce high quality sputter targets. Knowndestructive test methods, such as glow discharge mass spectroscopy andLECO techniques, are not suitable for this purpose.

Another factor affecting the quality of the layer or film produced by asputtering process is the presence of “flaws” in the sputter targetmaterial. As used herein, the term “flaws” refers to microscopicvolumetric defects in the sputter target material, such as inclusions,pores, cavities and micro-laminations. However, not all the flaws are“alike” in their degrading effect on sputter performance. Some types offlaws, for example, micro-cavities or shrinkage porosity causerelatively “mild” degrading effect on sputter performance while theothers, such as dielectric inclusions, cause a serious disturbance inthe sputter process. Therefore, there exists a corresponding need in theart for a non-destructive technique which identifies and separatelycounts different kinds of flaws which may exist in sputter targetmaterials.

FIG. 1 illustrates a prior art non-destructive ultrasonic “flaw”detection method for characterizing aluminum and aluminum alloy sputtertarget materials. The technique illustrated in FIG. 1 is similar to thatsuggested in Aluminum Pechiney PCT Application No. PCT/FR96/01959 foruse in classifying aluminum or aluminum alloy blanks suitable forfabricating sputter targets based on the size and number of internal“decohesions” detected per unit volume of the blanks.

The prior art technique of FIG. 1 employed a pulse-echo method performedon a test sample 10 having a planar upper surface 12 and a parallelplanar lower surface 14. In accordance with this technique, a focusedultrasonic transducer 16 irradiated a sequence of positions on the uppersurface 12 of the test sample 10 with a single, short-duration,high-frequency ultrasound pulse 18 having a frequency of at least 5 MHz,and preferably 10-50 MHz. The ultrasonic transducer 16 then switched toa sensing mode and detected a series of echoes 20 induced by theultrasound pulse 18.

One factor contributing to these echoes 20 was scattering of sonicenergy from the ultrasound pulse 18 by flaws 22 in the test sample 10.By comparing the amplitudes of echoes induced in the test sample 10 withthe amplitudes of echoes induced in reference samples (not shown) havingcompositions similar to that of the test sample 10 and blind,flat-bottomed holes of fixed depth and diameter, it was possible todetect and count flaws 22 in the test sample 10.

The number of flaws detected by the technique of FIG. 1 had to benormalized in order to facilitate comparison between test samples ofdifferent size and geometry. Conventionally, the number of flaws wasnormalized by volume—that is, the sputter target materials werecharacterized in units of “flaws per cubic centimeter.” The volumeassociated with the echoes 20 from each irradiation of the test sample10 was determined, in part, by estimating an effective cross-section ofthe pulse 18 in the test sample 10.

A portion of the scattered energy is attenuated by the material makingup the test sample 10. Furthermore, since the single flaw sizes ofinterest, which range from approximately 0.04 mm to 0.8 mm, are of samerange with the wavelength of ultrasound in metals (for example, thewavelength of sound in aluminum for the frequency range of 10 MHz to 50MHz is 0.6 mm to 0.12 mm respectively), the pulse 18 has a tendency torefract around the flaws 22, which reduces the scattering intensity.

Another factor detracting from the ability of the transducer 16 todetect the sonic energy scattered by the flaws 22 is the physical natureof the substance of the flaw or more accurately a degree of acousticimpedance mismatch at the flaw—matrix material boundary. The impedancemismatch directly affects the reflection and transmissioncharacteristics of ultrasound at the phase boundaries. The reflectioncoefficient of ultrasound beam at matrix-to-flaw boundary can beexpressed by the simplified expression: R=(I_(2-−I) ₁)/(I₂+I₁), where I₂is an acoustic impedance of the flaw material, and I, is an acousticimpedance of the matrix material. The simple analysis of this formulaallows us to derive several important conclusions. At first, if acousticimpedance of the flaw I₂ is less than the acoustic impedance of thematrix I₁, then the R coefficient becomes negative. The negativity ofthe R can be translated as a change in the phase of the acoustic pulsewaveform on 180°. For example, if the flaw is the gas-filled or vacuumed(shrinkage) void with the acoustic impedance equal to 0.93g/cm²-sec(×10⁶) (air) or below (vacuum), then the phase of theultrasound pulse waveform is changed on 180° at the boundary. At second,if the flaw is a gas filled or vacuumed void in the aluminum matrix withthe acoustic impedance of 17.2 g/cm²-sec(×10⁶), then the reflectioncoefficient value is close to the unity or 100% and the amplitude of thereflected signal is the only function of the relationship between flawsize and the ultrasound beam focal spot size. At third, if the flawcomprises a solid particle, for example, an alumina inclusion with theacoustic impedance of 39.6 g/cm²-sec(×10⁶), which exceeds the acousticimpedance of the aluminum matrix more than two times (17.2 g/cm²sec(×10⁶)), the ultrasound waveform does not experience the phaseinversion at the flaw boundary, and for alumina inclusion the reflectioncoefficient does not exceed 39.5% of the amplitude of the impingingpulse (if the wave interference effect is not considered). In this case,the amplitude of the reflected signal is the function of two variables,firstly, the relationship between flaw size and the beam focal spotsize, and secondly, the degree of acoustic impedance mismatch atflaw-to-matrix boundary.

Therefore, the final conclusion is that the void-like flaw and aluminainclusion of same size reflect the ultrasound energy quite differently.In addition to the waveform phase inversion, the amplitude of thereflected signal from the void-like flaw is at least two times higherthan for the alumina particle inclusion. Hence, the detectability ofalumina inclusions is generally poorer than the detectability ofvoid-like flaws, and if the phase information for reflected signal isnot extracted simultaneously with the amplitude information, the testingresults can be misleading caused by misinterpretation of the actuallarger alumina particle with the smaller void-like flaw and vice versa.

Another factor detracting from the ability of the transducer 16 todetect the sonic energy scattered by the flaws 22 is the noise generatedby scattering of the pulse 18 at the boundaries between grains havingdifferent textures. In fact, the texture-related noise can be so greatfor high-purity aluminum having grain sizes on the order of severalmillimeters that small flaws within a size range of approximately 0.05mm and less cannot be detected. Larger grain sizes reduce thesignal-to-noise ratio for the sonic energy scattered by the flaws whencompared to the noise induced by the grain boundaries.

Other factors affecting the sensitivity and resolution of the techniqueof FIG. 1 include the pulse frequency, duration and waveform; the degreeof beam focus and the focal spot size; the coupling conditions (that is,the efficiency with which the sonic energy travels from the transducer16 to the test sample 10); and the data acquisition system parameters.

One major drawback to the technique of FIG. 1 is an inability of thetechnique to distinguish between different sorts of flaws, particularlybetween void-like flaws and solid particle inclusions, such as aluminaparticles. This technique, which relies only on the echo amplitudemeasurements, confirms only the physical existence of the flaw. Itsphysical nature and actual size are not properly revealed and derivedonly on the basis of the flaw type assumption. If the internal“decohesions” (void-like defects) are the only defects in the targetmaterial, then the technique as referred in the method (FIG. 1) is ableto detect and size defects adequately. However, in reality the internal“decohesions” as referred in the method (FIG. 1), are the fraction ofplurality of defect types which may exist in the target material. Forexample, the metallographic evaluation revealed also aluminum oxideparticles in the aluminum for sputter targets. Therefore, the techniqueas referred in the method (FIG. 1) is unable to distinguish and todifferentiate between pluralities of flaw types since the waveform phasechange information remains not revealed.

Thus, there remains a need in the art for non-destructive techniques forcharacterizing sputter target materials having different pluralities offlaw types. There also remains a need for a technique that separatelycompares the target intrinsic volumetric cleanliness for the specificgroups of flaws such as void-like flaws (cavities, microlaminations,“decohesions”) and solid inclusions.

One imaging technique implemented by Sonix, Inc. (8700 Morrisette Dr.,Springfield, Va. 22152) in a FlexSCAN-C C-scanning uses a phase gatingmethod which detects the phase inversion in the waveform at thematrix-to-flaw boundary. The technique uses a “Texas Instruments” phaseinversion algorithm (licensed to SONIX, Inc.). The technique maps theflaws on a two-dimensional sample image only if the 180° phase change isdetected. Therefore, this technique is limited to detection and mappingvoid-like defects when the impedance is changed from higher to lower atthe flaw boundary. For sputter target applications however, it isabsolutely necessary to detect and identify the aluminaparticle-inclusions, and the phase inversion technique used by theSonix. Inc. does not work in this case since the waveform does notchange its phase at the flaw boundary.

There also remains a need for a technique that separately detects andsizes specific alumina particle-inclusions.

SUMMARY OF THE INVENTION

These needs and others are addressed by a non-destructive method forcharacterizing a sputter target material comprising the steps ofsequentially irradiating a test sample of the sputter target materialwith sonic energy at a plurality of positions on a surface of thesample; detecting echoes induced by the sonic energy; discriminatingtexture-related backscattering noise from the echoes to obtainnon-rectified radio frequency echo waveform signals; monitoringnon-rectified echo waveform signals for the 180° waveform phaseinversion, comparing the non-rectified echo waveform signals with saidat least one of each: phase inverting and phase non-inverting referencevalues, to detect void-like and particle-like flaw data pointsseparately and no-flaw data points; counting the flaw data points forthe each flaw type separately as well as all together to determine atotal flaw count C_(FT(TOTAL)); C_(FI(with phase inversion)), flaw countwithout phase inversion C_(FN(without phase inversion)), counting theflaw data points and the no-flaw data points to determine a total numberof data points C_(DP) and calculating a total cleanliness factorF_(CT)=(C_(FT)/C_(DP))×10⁶ as well as cleanliness factorsF_(CI)=(C_(FI)/C_(DP))×10⁶ and F_(C)=(C_(FN)/C_(DP))×10⁶ for each sortof flaws separately.

Unlike the prior art method described earlier, the method of the presentinvention provides a characterization of the sputter target material byseparately identifying and counting void-like and particle-like flaws. Apartition of cleanliness factor for components associated with differentkinds of flaws tunes up the rejection criteria more precisely byidentifying and sizing the flaws of different kind.

Unlike the Sonix, Inc. method, the method of the present inventionprovides a characterization of both the waveform phase inverting andphase non-inverting flaws. Therefore, there is a smaller risk to missthe waveform phase non-inverting flaws which are of a primary concernfor sputter target applications.

Although the cleanliness factor technique provides a usefulcharacterization of the sputter target material, more information can beprovided by means of a histogram. More specifically, the sputter targettest method may be characterized by defining a plurality of amplitudebands for each type (waveform inverting and non-inverting) of flaws;measuring said modified amplitude signals to determine modifiedamplitude signal magnitudes; comparing said modified amplitude signalmagnitudes with said plurality of amplitude bands to form subsets ofsaid modified amplitude signals; counting said subsets of modifiedamplitude signals to determine a plurality of modified amplitude signalcounts, each modified amplitude signal count of said plurality ofamplitude signal counts corresponding to one of said amplitude bands ofsaid plurality of amplitude bands; and constructing a pareto histogram,combining individual histograms for both flaw classes, relating saidmodified signals counts to said plurality of amplitude bands. Since thehistogram does not attempt to directly map the locations of flaws alongthe surface of the sputter target material, it does not suffer from thescaling problems.

Most preferably, the test sample is compressed along one dimension, suchas by rolling or forging, and then irradiated by sonic energypropagating transversely (that is, obliquely or, better yet, normally)to that dimension. This has the additional effect of flattening andwidening of certain flaws (aluminum oxide film clusters and voids) inthe material. The widening of the flaws, in turn, increases theintensity of the sonic energy scattered by the flaws and reduces thelikelihood that the sonic energy will refract around the flaws.

These methods for characterizing sputter target materials may be used inprocesses for manufacturing sputter targets. As noted earlier, thecleanliness of a sputter target and particularly cleanliness fromnon-phase inverting flaws is the primary factor determining the qualityof the layers or films produced by the target. By shaping only thosesputter target blanks having cleanliness factors or histograms meetingcertain reference criteria to form sputter targets, and rejecting blanksnot meeting those criteria, one improves the likelihood that the sputtertargets so manufactured will produce high quality layers or films.

Therefore, it is one object of the invention to provide non-destructivemethods for characterizing sputter target materials. Other objects ofthe invention will be apparent from the follow description, theaccompanying drawings and the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view illustrating of prior art method ofultrasonic texture analysis;

FIG. 2 is a perspective view illustrating an especially preferred testsample, prior to compressing, used for cleanliness characterization inaccordance with the invention;

FIG. 3 is a schematic view illustrating an especially preferred methodof ultrasonic cleanliness characterization, utilizing a compressedversion of the test sample as shown in FIG. 2, in accordance with theinvention;

FIG. 4 is a schematic view of a test apparatus for carrying out themethod of FIG. 3;

FIG. 5 is a histogram characterizing a relatively “clean” Al-0.5 wt % Cumaterial in accordance with an especially preferred form of theinvention; and

FIG. 6 is a histogram characterizing a less “clean” Al-0.5 wt % Cumaterial in accordance with the especially preferred form of theinvention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 3 illustrates an especially preferred method for sorting of flawsand characterizing the cleanliness of sputter target material. Inaccordance with this method, a cylindrical sample 50 of the sputtertarget material (which preferably comprises metal or a metal alloy) iscompressed or worked to produce a disc-shaped test sample 52 having aplanar upper surface 54 and a planar lower surface 56 approximatelyparallel to the upper surface 54. Thereafter, a focused ultrasonictransducer 60 is positioned near the upper surface 54. The transducer 60irradiates the upper surface 54 of the test sample 52 with a single,short-duration, MHz frequency range pulse of sonic energy 62. Thetransducer 60 subsequently detects an echo 64 induced in the test sample52 by the pulse of sonic energy 62. The transducer 60 converts the echointo an electrical radio frequency signal (not shown), which isprocessed to retrieve the waveform phase and maximum amplitudeinformation.

More specifically, the sample 50, as shown in FIG. 2, first iscompressed along a dimension 70 to form the disc-shaped test sample 52as shown in FIG. 3. Preferably, the sample 50 is compressed by forgingor rolling of the sample 50, followed by diamond cutting to prepare theplanar surfaces 54 and 56. The reduction in the dimension 70 may beanywhere between 0% to 100%. The compression of the sample 50 flattensand widens certain flaws 72 to increase their surface area normal to thedimension 70.

As illustrated in FIG. 4, the test sample 52 is immersed in deionizedwater (not shown) in a conventional immersion tank 80. The transducer 60is mounted on a mechanical X-Y scanner 82 in electrical communicationwith a controller 84 such as a PC controller. The controller 84 isprogrammed in a conventional manner to induce the mechanical X-Yscanning unit 82 to move the transducer 60 in a raster-like stepwisemotion across the upper surface 54 of the test sample 52.

Again, with respect to FIG. 3, the presently preferred transducer 60 issold by ULTRAN USA under the designation WS50-10P4.5. This is a longfocal length piezoelectric transducer having a fixed focal length of 114mm (in water). At a peak frequency of approximately 9.15 MHz with 8 MHz(−6 dB) bandwidth, the transducer produces a pulse of sonic energy 62having a focal zone (−6 dB) of approximately 21 mm in aluminum and afocal spot 0.8-0.9 mm in diameter.

Most preferably, the upper surface 54 of the sample 52 has a width ordiameter on the order of approximately 28 cm. Data acquisition steps ofapproximately 0.9 mm in both the “x”-direction and the “y”-directionpermit the detection of 0.25 mm flat bottom holes at a detection levelof −6 dB without exposure area overlap. One thereby irradiatesapproximately 100,000 test points on the upper surface 54.

Most preferably, the transducer 60 is oriented so that the pulse ofsonic energy 62 propagates through the deionized water (not shown) inthe immersion tank 80 and strikes the test sample 52 approximatelynormal to the upper surface 54. Furthermore, the transducer 60 ispreferably spaced from the upper surface 54 such that the pulse of sonicenergy 62 is focused on a zone 86 of the test sample 52 betweenapproximately 3 mm and 24 mm below the upper surface 54. The pulse ofsonic energy 62 interacts with the sample 52 to induce echoes 64, whichthen propagate back through the deionized water (not shown) to thetransducer 60 approximately 60 μsec after the pulse of sonic energy 62is sent.

Turning back to FIG. 4, an especially preferred echo acquisition systemincludes a low noise receiver comprising a low noise gated preamplifier90; a low noise linear amplifier 92 with a set of calibratedattenuators, a 12-bit (2.44 mV/bit) analog-to-digital converter 94 anddigital oscilloscope 95 connected with receiver analog output. Whensufficient time has elapsed for the echoes to arrive at the transducer60, the controller 84 switches the transducer 60 from a transmittingmode to a gated electronic receiving mode. The echoes 64 are received bythe transducer 60 and converted into an RF electric signal (not shown).The RF signal is amplified by the preamplifier 90 and by the low noiselinear amplifier 92 to produce modified amplitude signal and displayedon the screen of oscilloscope 95 to extract waveform phase information.The modified amplitude signal then is digitized by the analog-to-digitalconverter 94 before moving on to the controller 84. Theanalog-to-digital conversion is performed so as to preserve amplitudeinformation from the analog modified amplitude signal.

Flaws of given nature (void-like or alumina inclusions) are determinedby monitoring for waveform phase inversion using digital oscilloscope95. Flaws of given sizes are detected by comparing the digitizedmodified amplitude signals obtained from the sample 52 with referencevalues (or calibration values) derived from tests conducted on referencesamples (not shown) having compositions similar to those of the testsample 10 and either blind, flat-bottomed holes of fixed depth anddiameter or alumina particles of given size artificially imbedded intoreference sample material.

The especially preferred PC controller 84 controls the data acquisitionprocess. An especially preferred software package used in connectionwith the data acquisition system is available from StructuralDiagnostics, Inc. under the designation SDI-5311 Winscan.

The PC controller 84 is also programmed to calculate the totalcleanliness factor and the cleanliness factors for the sorted flawscharacterization the material of the samples 50, 52. More precisely, itis programmed to discriminate texture-related backscattering noise andto distinguish “void-like flaw data points from the aluminaparticle-like flaw data points.” The PC controller 84 maintains a countof the flaw data points detected during the testing of a test sample 52to determine a flaw count “C_(FT)” “C_(FI),” “C_(FM)”.

The PC controller 84 also is programmed to distinguish “no-flaw datapoints,” that is, digitized modified amplitude signals representingamplitudes which, after comparison with the reference values, indicatethe absence of flaws.

The PC controller also determines a total number of data points“C_(DP),” that is, the sum of the flaw count CF and the number ofno-flaw data points. Although the total number of data points could bedetermined by maintaining counts of the flaw data points and the no-flawdata points, it is preferably determined by counting the total number ofpositions “C_(I)” along the upper surface 54 at which the test sample 52is irradiated by the transducer 60 and subtracting the number ofdigitized RF signals “C_(N)” which the data acquisition circuitry wasunable, due to noise or other causes, to identify as either flaw datapoints or no-flaw data points. (Alternatively, the “noise count” C_(N)may be described as the number of positions along the upper surface 54at which neither a flaw data point nor a no-flaw data point isdetected.)

Having determined the flaw counts C_(FT), C_(FI), C_(FN), and the totalnumber of data points C_(DP), the PC controller is programmed tocalculate the cleanliness factor F_(C)=(C_(FT)/C_(DP))×10⁶,F_(CN)=(C_(FI)/C_(DP))×10⁶, C_(N)=(C_(FN)/C_(DP))×10⁶ to characterizethe material comprising the samples 50, 52. Unlike the prior art “flawsper cubic centimeter,” the magnitude of the cleanliness factor is notdependent on any estimate of pulse cross-sectional area. Since thecleanliness factor is normalized by the dimensionless coefficientC_(DP)×10⁻⁶ rather than by volume, it is more closely related to ppm andppb units than are units of “flaws per cubic centimeter.”

The preparation of a suitable program for determining the cleanlinessfactor in accordance with the invention as disclosed herein is withinthe ordinary skill in the art and requires no undue experimentation.

Another way in which to characterize the material comprising the samples50, 52 is by determining the size distribution of flaws in the testsample 52. More specifically, one may characterize the cleanliness ofthe sample 52 by defining amplitude bands or ranges; comparing theamplitudes represented by the digitized modified amplitude signal forcertain types of flaws (phase inverting and phase non-inverting) withthe amplitude bands to form subsets of the modified amplitude signals;counting these subsets of modified amplitude signals to determine amodified amplitude signal counts for each amplitude band and for eachtype of flaws; and constructing a pareto histogram relating the modifiedsignal counts to said plurality of amplitude bands. Since the amplitudesrepresented by the digitized modified amplitude signals for each type offlaws are related to the sizes of flaws detected in the sample 52, thehistogram provides an indication of the flaw size distribution in thesample 52.

Turning now to FIGS. 5 and 6, there may be seen pareto histogramscharacterizing two Al-0.5 wt % Cu alloy sputter target materials havingorthorhombic textures and grain sizes in the range of 0.08 mm to 0.12mm. The material of FIG. 5 was “cleaner” than that of FIG. 6; thematerial of FIG. 5 had a cleanliness factor C_(FT) of 250 and C_(FN) of100 while the material of FIG. 6 had a cleanliness factor C_(F) of 1,200and C_(FN) of 300. It is important to emphasize that for sputteringapplications to have a lower C_(FN) value is more important than to havethe lower C_(FT) value. The zone of flaw monitoring was located within agate of seven microsecond duration with a gate delay of 1 microsecond.

The abscissa 155 of the pareto histogram of FIG. 5 represents theamplitude normalized as a percentage of the echo amplitude induced in areference sample having a 0.8 mm blind, flat-bottomed hole. The ordinate157 in FIG. 5 represents the modified signal counts for each amplitude,expressed on a logarithmic scale. The echo amplitude threshold for theflaw counting was set to 12% since, as established experimentally, thetexture-related echo amplitude did not exceed 10% for all aluminumalloys tested. The abscissa 161 and ordinate 163 of the histogram ofFIG. 6 were scaled similarly.

The histograms of FIGS. 4 and 5 represent an improvement over prior artimaging techniques in that the distribution of flaw sizes may berepresented without having to represent flaw sizes relative to thesurface area of the test sample (not shown).

The preparation of a suitable program for plotting histograms such asthose shown in FIGS. 5 and 6 in accordance with the invention asdisclosed herein is within the ordinary skill in the art and requires noundue experimentation. Either the cleanliness factor or histograms suchas those shown in FIGS. 5 and 6 may be used in a process formanufacturing sputter targets. As noted earlier, the cleanliness of asputter target is one factor determining the quality of the layers orfilms produced by the target. By shaping only those sputter targetblanks having cleanliness factors and particularly C_(FN) less thanreference cleanliness factors, or having histograms with selectedcolumns or areas less than reference values, to form sputter targets,and rejecting blanks not meeting those criteria, one improves thelikelihood that the sputter targets so manufactured will produce highquality layers or films.

While the method herein described, and the form of apparatus forcarrying this method into effect, constitute a preferred embodiment ofthis invention, it is to be understood that the invention is not limitedto this precise method and form of apparatus, and that changes may bemade in either without departing from the scope of the invention, whichis defined in the appended claims.

What is claimed is:
 1. A non-destructive method for characterizingsputter target material, comprising the steps: a) obtaining a referencevalue for waveform phase inverting flaws and a reference value forwaveform phase non-inverting flaws utilizing a reference sample; b)irradiating a test sample of said sputter target material sequentiallywith sonic energy at a plurality of positions along a surface of saidtest sample; c) detecting radio frequency echo waveforms induced by saidsonic energy; d) discriminating texture-related backscattering noisefrom said echo waveforms to obtain a radio frequency echo waveformsignal; e) monitoring said radio frequency echo waveform signal for 180°waveform phase inversion; f) comparing the radio frequency echo waveformsignal associated with each of said plurality of positions with saidwaveform phase inverting reference value and said waveform phasenon-inverting reference value and obtaining individual data pointsassociated with a void-like flaw, a particle-like flaw and no-flaw; g)counting the data points associated with waveform phase inverting flaws,waveform phase non-inverting flaws, and no-flaws to determine a flawcount associated with waveform phase inversion flaws C_(FI), a flawcount associated with waveform phase non-inversion flaws C_(FN), a totalflaw count C_(FT), and a total number of data points C_(DP); and h)calculating a total cleanliness factor F^(CT)=(C_(FT)/C_(DP))×10⁶, acleanliness factor associated with phase inversion flawsF_(CI)=(C_(FI)/C_(DP))×10⁶ and a cleanliness factor associated withphase non-inversion flaws F_(C)=(C_(FN)/C_(DP))×10⁶.
 2. Anon-destructive method for characterizing sputter target material as inclaim 1, wherein said reference sample comprises blind, flat-bottomed,holes of fixed depth and diameter.
 3. A non-destructive method forcharacterizing sputter target material as in claim 1, wherein saidreference sample comprises alumna particles of given size artificiallyimbedded.
 4. A non-destructive method for characterizing sputter targetmaterial as in claim 1, wherein said test sample is a cylindricalportion of said sputter target material.
 5. A non-destructive method forcharacterizing sputter target material as in claim 4, wherein saidcylindrical portion is formed into a disc-shaped test sample.
 6. Anon-destructive method for characterizing sputter target material as inclaim 5, wherein said disc-shaped test sample is formed by rolling saidcylindrical portion.
 7. A non-destructive method for characterizingsputter target material as in claim 5, wherein said disc-shaped testsample is formed by forging said cylindrical portion.
 8. Anon-destructive method for characterizing sputter target material as inclaim 5, wherein said disc-shaped test sample comprises first and secondplanar surfaces.
 9. A non-destructive method for characterizing sputtertarget material as in claim 8, wherein said first and second planarsurfaces are prepared by diamond cutting.
 10. A non-destructive methodfor characterizing sputter target material as in claim 1, wherein saidsonic energy is generated by a transducer.
 11. A non-destructive methodfor characterizing sputter target material as in claim 10, furthercomprising the step: immersing said test sample in deionized waterwithin an immersion tank and orienting said transducer such that saidsonic energy propagates through said deionized water striking said testsample substantially normal to an upper surface of said test sample. 12.A non-destructive method for characterizing sputter target material asin claim 10, wherein: said transducer is piezoelectric and comprises afixed focal length in water of approximately 114 mm, a peak frequency ofapproximately 9.15 MHz with approximately 8 MHz (−6 dB) bandwidth; andsaid transducer produces a pulse having a focal zone (−6 dB) ofapproximately 21 mm in aluminum and a focal spot 0.8-0.9 mm in diameter.13. A non-destructive method for characterizing sputter target materialas in claim 12, wherein: said test sample comprises an upper surfacewith a width on the order of approximately 28 cm; and obtaining saiddata points in raster-like stepwise motion in steps approximately 0.9 mmin both a x-direction and a y-direction over the entire said uppersurface.